mirror of
https://github.com/opencv/opencv.git
synced 2024-12-21 13:48:04 +08:00
374 lines
13 KiB
C++
374 lines
13 KiB
C++
/* This is sample from the OpenCV book. The copyright notice is below */
|
|
|
|
/* *************** License:**************************
|
|
Oct. 3, 2008
|
|
Right to use this code in any way you want without warranty, support or any guarantee of it working.
|
|
|
|
BOOK: It would be nice if you cited it:
|
|
Learning OpenCV: Computer Vision with the OpenCV Library
|
|
by Gary Bradski and Adrian Kaehler
|
|
Published by O'Reilly Media, October 3, 2008
|
|
|
|
AVAILABLE AT:
|
|
http://www.amazon.com/Learning-OpenCV-Computer-Vision-Library/dp/0596516134
|
|
Or: http://oreilly.com/catalog/9780596516130/
|
|
ISBN-10: 0596516134 or: ISBN-13: 978-0596516130
|
|
|
|
OPENCV WEBSITES:
|
|
Homepage: http://opencv.org
|
|
Online docs: http://docs.opencv.org
|
|
Q&A forum: http://answers.opencv.org
|
|
Issue tracker: http://code.opencv.org
|
|
GitHub: https://github.com/opencv/opencv/
|
|
************************************************** */
|
|
|
|
#include "opencv2/calib3d.hpp"
|
|
#include "opencv2/imgcodecs.hpp"
|
|
#include "opencv2/highgui.hpp"
|
|
#include "opencv2/imgproc.hpp"
|
|
|
|
#include <vector>
|
|
#include <string>
|
|
#include <algorithm>
|
|
#include <iostream>
|
|
#include <iterator>
|
|
#include <stdio.h>
|
|
#include <stdlib.h>
|
|
#include <ctype.h>
|
|
|
|
using namespace cv;
|
|
using namespace std;
|
|
|
|
static int print_help()
|
|
{
|
|
cout <<
|
|
" Given a list of chessboard images, the number of corners (nx, ny)\n"
|
|
" on the chessboards, and a flag: useCalibrated for \n"
|
|
" calibrated (0) or\n"
|
|
" uncalibrated \n"
|
|
" (1: use cvStereoCalibrate(), 2: compute fundamental\n"
|
|
" matrix separately) stereo. \n"
|
|
" Calibrate the cameras and display the\n"
|
|
" rectified results along with the computed disparity images. \n" << endl;
|
|
cout << "Usage:\n ./stereo_calib -w=<board_width default=9> -h=<board_height default=6> -s=<square_size default=1.0> <image list XML/YML file default=../data/stereo_calib.xml>\n" << endl;
|
|
return 0;
|
|
}
|
|
|
|
|
|
static void
|
|
StereoCalib(const vector<string>& imagelist, Size boardSize, float squareSize, bool displayCorners = false, bool useCalibrated=true, bool showRectified=true)
|
|
{
|
|
if( imagelist.size() % 2 != 0 )
|
|
{
|
|
cout << "Error: the image list contains odd (non-even) number of elements\n";
|
|
return;
|
|
}
|
|
|
|
const int maxScale = 2;
|
|
// ARRAY AND VECTOR STORAGE:
|
|
|
|
vector<vector<Point2f> > imagePoints[2];
|
|
vector<vector<Point3f> > objectPoints;
|
|
Size imageSize;
|
|
|
|
int i, j, k, nimages = (int)imagelist.size()/2;
|
|
|
|
imagePoints[0].resize(nimages);
|
|
imagePoints[1].resize(nimages);
|
|
vector<string> goodImageList;
|
|
|
|
for( i = j = 0; i < nimages; i++ )
|
|
{
|
|
for( k = 0; k < 2; k++ )
|
|
{
|
|
const string& filename = imagelist[i*2+k];
|
|
Mat img = imread(filename, 0);
|
|
if(img.empty())
|
|
break;
|
|
if( imageSize == Size() )
|
|
imageSize = img.size();
|
|
else if( img.size() != imageSize )
|
|
{
|
|
cout << "The image " << filename << " has the size different from the first image size. Skipping the pair\n";
|
|
break;
|
|
}
|
|
bool found = false;
|
|
vector<Point2f>& corners = imagePoints[k][j];
|
|
for( int scale = 1; scale <= maxScale; scale++ )
|
|
{
|
|
Mat timg;
|
|
if( scale == 1 )
|
|
timg = img;
|
|
else
|
|
resize(img, timg, Size(), scale, scale);
|
|
found = findChessboardCorners(timg, boardSize, corners,
|
|
CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_NORMALIZE_IMAGE);
|
|
if( found )
|
|
{
|
|
if( scale > 1 )
|
|
{
|
|
Mat cornersMat(corners);
|
|
cornersMat *= 1./scale;
|
|
}
|
|
break;
|
|
}
|
|
}
|
|
if( displayCorners )
|
|
{
|
|
cout << filename << endl;
|
|
Mat cimg, cimg1;
|
|
cvtColor(img, cimg, COLOR_GRAY2BGR);
|
|
drawChessboardCorners(cimg, boardSize, corners, found);
|
|
double sf = 640./MAX(img.rows, img.cols);
|
|
resize(cimg, cimg1, Size(), sf, sf);
|
|
imshow("corners", cimg1);
|
|
char c = (char)waitKey(500);
|
|
if( c == 27 || c == 'q' || c == 'Q' ) //Allow ESC to quit
|
|
exit(-1);
|
|
}
|
|
else
|
|
putchar('.');
|
|
if( !found )
|
|
break;
|
|
cornerSubPix(img, corners, Size(11,11), Size(-1,-1),
|
|
TermCriteria(TermCriteria::COUNT+TermCriteria::EPS,
|
|
30, 0.01));
|
|
}
|
|
if( k == 2 )
|
|
{
|
|
goodImageList.push_back(imagelist[i*2]);
|
|
goodImageList.push_back(imagelist[i*2+1]);
|
|
j++;
|
|
}
|
|
}
|
|
cout << j << " pairs have been successfully detected.\n";
|
|
nimages = j;
|
|
if( nimages < 2 )
|
|
{
|
|
cout << "Error: too little pairs to run the calibration\n";
|
|
return;
|
|
}
|
|
|
|
imagePoints[0].resize(nimages);
|
|
imagePoints[1].resize(nimages);
|
|
objectPoints.resize(nimages);
|
|
|
|
for( i = 0; i < nimages; i++ )
|
|
{
|
|
for( j = 0; j < boardSize.height; j++ )
|
|
for( k = 0; k < boardSize.width; k++ )
|
|
objectPoints[i].push_back(Point3f(k*squareSize, j*squareSize, 0));
|
|
}
|
|
|
|
cout << "Running stereo calibration ...\n";
|
|
|
|
Mat cameraMatrix[2], distCoeffs[2];
|
|
cameraMatrix[0] = initCameraMatrix2D(objectPoints,imagePoints[0],imageSize,0);
|
|
cameraMatrix[1] = initCameraMatrix2D(objectPoints,imagePoints[1],imageSize,0);
|
|
Mat R, T, E, F;
|
|
|
|
double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1],
|
|
cameraMatrix[0], distCoeffs[0],
|
|
cameraMatrix[1], distCoeffs[1],
|
|
imageSize, R, T, E, F,
|
|
CALIB_FIX_ASPECT_RATIO +
|
|
CALIB_ZERO_TANGENT_DIST +
|
|
CALIB_USE_INTRINSIC_GUESS +
|
|
CALIB_SAME_FOCAL_LENGTH +
|
|
CALIB_RATIONAL_MODEL +
|
|
CALIB_FIX_K3 + CALIB_FIX_K4 + CALIB_FIX_K5,
|
|
TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 100, 1e-5) );
|
|
cout << "done with RMS error=" << rms << endl;
|
|
|
|
// CALIBRATION QUALITY CHECK
|
|
// because the output fundamental matrix implicitly
|
|
// includes all the output information,
|
|
// we can check the quality of calibration using the
|
|
// epipolar geometry constraint: m2^t*F*m1=0
|
|
double err = 0;
|
|
int npoints = 0;
|
|
vector<Vec3f> lines[2];
|
|
for( i = 0; i < nimages; i++ )
|
|
{
|
|
int npt = (int)imagePoints[0][i].size();
|
|
Mat imgpt[2];
|
|
for( k = 0; k < 2; k++ )
|
|
{
|
|
imgpt[k] = Mat(imagePoints[k][i]);
|
|
undistortPoints(imgpt[k], imgpt[k], cameraMatrix[k], distCoeffs[k], Mat(), cameraMatrix[k]);
|
|
computeCorrespondEpilines(imgpt[k], k+1, F, lines[k]);
|
|
}
|
|
for( j = 0; j < npt; j++ )
|
|
{
|
|
double errij = fabs(imagePoints[0][i][j].x*lines[1][j][0] +
|
|
imagePoints[0][i][j].y*lines[1][j][1] + lines[1][j][2]) +
|
|
fabs(imagePoints[1][i][j].x*lines[0][j][0] +
|
|
imagePoints[1][i][j].y*lines[0][j][1] + lines[0][j][2]);
|
|
err += errij;
|
|
}
|
|
npoints += npt;
|
|
}
|
|
cout << "average epipolar err = " << err/npoints << endl;
|
|
|
|
// save intrinsic parameters
|
|
FileStorage fs("intrinsics.yml", FileStorage::WRITE);
|
|
if( fs.isOpened() )
|
|
{
|
|
fs << "M1" << cameraMatrix[0] << "D1" << distCoeffs[0] <<
|
|
"M2" << cameraMatrix[1] << "D2" << distCoeffs[1];
|
|
fs.release();
|
|
}
|
|
else
|
|
cout << "Error: can not save the intrinsic parameters\n";
|
|
|
|
Mat R1, R2, P1, P2, Q;
|
|
Rect validRoi[2];
|
|
|
|
stereoRectify(cameraMatrix[0], distCoeffs[0],
|
|
cameraMatrix[1], distCoeffs[1],
|
|
imageSize, R, T, R1, R2, P1, P2, Q,
|
|
CALIB_ZERO_DISPARITY, 1, imageSize, &validRoi[0], &validRoi[1]);
|
|
|
|
fs.open("extrinsics.yml", FileStorage::WRITE);
|
|
if( fs.isOpened() )
|
|
{
|
|
fs << "R" << R << "T" << T << "R1" << R1 << "R2" << R2 << "P1" << P1 << "P2" << P2 << "Q" << Q;
|
|
fs.release();
|
|
}
|
|
else
|
|
cout << "Error: can not save the extrinsic parameters\n";
|
|
|
|
// OpenCV can handle left-right
|
|
// or up-down camera arrangements
|
|
bool isVerticalStereo = fabs(P2.at<double>(1, 3)) > fabs(P2.at<double>(0, 3));
|
|
|
|
// COMPUTE AND DISPLAY RECTIFICATION
|
|
if( !showRectified )
|
|
return;
|
|
|
|
Mat rmap[2][2];
|
|
// IF BY CALIBRATED (BOUGUET'S METHOD)
|
|
if( useCalibrated )
|
|
{
|
|
// we already computed everything
|
|
}
|
|
// OR ELSE HARTLEY'S METHOD
|
|
else
|
|
// use intrinsic parameters of each camera, but
|
|
// compute the rectification transformation directly
|
|
// from the fundamental matrix
|
|
{
|
|
vector<Point2f> allimgpt[2];
|
|
for( k = 0; k < 2; k++ )
|
|
{
|
|
for( i = 0; i < nimages; i++ )
|
|
std::copy(imagePoints[k][i].begin(), imagePoints[k][i].end(), back_inserter(allimgpt[k]));
|
|
}
|
|
F = findFundamentalMat(Mat(allimgpt[0]), Mat(allimgpt[1]), FM_8POINT, 0, 0);
|
|
Mat H1, H2;
|
|
stereoRectifyUncalibrated(Mat(allimgpt[0]), Mat(allimgpt[1]), F, imageSize, H1, H2, 3);
|
|
|
|
R1 = cameraMatrix[0].inv()*H1*cameraMatrix[0];
|
|
R2 = cameraMatrix[1].inv()*H2*cameraMatrix[1];
|
|
P1 = cameraMatrix[0];
|
|
P2 = cameraMatrix[1];
|
|
}
|
|
|
|
//Precompute maps for cv::remap()
|
|
initUndistortRectifyMap(cameraMatrix[0], distCoeffs[0], R1, P1, imageSize, CV_16SC2, rmap[0][0], rmap[0][1]);
|
|
initUndistortRectifyMap(cameraMatrix[1], distCoeffs[1], R2, P2, imageSize, CV_16SC2, rmap[1][0], rmap[1][1]);
|
|
|
|
Mat canvas;
|
|
double sf;
|
|
int w, h;
|
|
if( !isVerticalStereo )
|
|
{
|
|
sf = 600./MAX(imageSize.width, imageSize.height);
|
|
w = cvRound(imageSize.width*sf);
|
|
h = cvRound(imageSize.height*sf);
|
|
canvas.create(h, w*2, CV_8UC3);
|
|
}
|
|
else
|
|
{
|
|
sf = 300./MAX(imageSize.width, imageSize.height);
|
|
w = cvRound(imageSize.width*sf);
|
|
h = cvRound(imageSize.height*sf);
|
|
canvas.create(h*2, w, CV_8UC3);
|
|
}
|
|
|
|
for( i = 0; i < nimages; i++ )
|
|
{
|
|
for( k = 0; k < 2; k++ )
|
|
{
|
|
Mat img = imread(goodImageList[i*2+k], 0), rimg, cimg;
|
|
remap(img, rimg, rmap[k][0], rmap[k][1], INTER_LINEAR);
|
|
cvtColor(rimg, cimg, COLOR_GRAY2BGR);
|
|
Mat canvasPart = !isVerticalStereo ? canvas(Rect(w*k, 0, w, h)) : canvas(Rect(0, h*k, w, h));
|
|
resize(cimg, canvasPart, canvasPart.size(), 0, 0, INTER_AREA);
|
|
if( useCalibrated )
|
|
{
|
|
Rect vroi(cvRound(validRoi[k].x*sf), cvRound(validRoi[k].y*sf),
|
|
cvRound(validRoi[k].width*sf), cvRound(validRoi[k].height*sf));
|
|
rectangle(canvasPart, vroi, Scalar(0,0,255), 3, 8);
|
|
}
|
|
}
|
|
|
|
if( !isVerticalStereo )
|
|
for( j = 0; j < canvas.rows; j += 16 )
|
|
line(canvas, Point(0, j), Point(canvas.cols, j), Scalar(0, 255, 0), 1, 8);
|
|
else
|
|
for( j = 0; j < canvas.cols; j += 16 )
|
|
line(canvas, Point(j, 0), Point(j, canvas.rows), Scalar(0, 255, 0), 1, 8);
|
|
imshow("rectified", canvas);
|
|
char c = (char)waitKey();
|
|
if( c == 27 || c == 'q' || c == 'Q' )
|
|
break;
|
|
}
|
|
}
|
|
|
|
|
|
static bool readStringList( const string& filename, vector<string>& l )
|
|
{
|
|
l.resize(0);
|
|
FileStorage fs(filename, FileStorage::READ);
|
|
if( !fs.isOpened() )
|
|
return false;
|
|
FileNode n = fs.getFirstTopLevelNode();
|
|
if( n.type() != FileNode::SEQ )
|
|
return false;
|
|
FileNodeIterator it = n.begin(), it_end = n.end();
|
|
for( ; it != it_end; ++it )
|
|
l.push_back((string)*it);
|
|
return true;
|
|
}
|
|
|
|
int main(int argc, char** argv)
|
|
{
|
|
Size boardSize;
|
|
string imagelistfn;
|
|
bool showRectified;
|
|
cv::CommandLineParser parser(argc, argv, "{w|9|}{h|6|}{s|1.0|}{nr||}{help||}{@input|../data/stereo_calib.xml|}");
|
|
if (parser.has("help"))
|
|
return print_help();
|
|
showRectified = !parser.has("nr");
|
|
imagelistfn = parser.get<string>("@input");
|
|
boardSize.width = parser.get<int>("w");
|
|
boardSize.height = parser.get<int>("h");
|
|
float squareSize = parser.get<float>("s");
|
|
if (!parser.check())
|
|
{
|
|
parser.printErrors();
|
|
return 1;
|
|
}
|
|
vector<string> imagelist;
|
|
bool ok = readStringList(imagelistfn, imagelist);
|
|
if(!ok || imagelist.empty())
|
|
{
|
|
cout << "can not open " << imagelistfn << " or the string list is empty" << endl;
|
|
return print_help();
|
|
}
|
|
|
|
StereoCalib(imagelist, boardSize, squareSize, false, true, showRectified);
|
|
return 0;
|
|
}
|